Quantum Regression Algorithm

Quantum regression algorithms aim to leverage quantum computing to improve the speed and efficiency of regression analysis, a fundamental task in machine learning and data analysis. Current research focuses on developing and analyzing various quantum algorithms, including those based on quantum annealing, variational quantum circuits (VQCs), and quantum linear algebra techniques, often incorporating classical-quantum hybrid approaches. These efforts seek to achieve speedups over classical methods, particularly for high-dimensional datasets, and to enhance model interpretability. The successful development of these algorithms could significantly impact fields requiring large-scale regression analysis, such as materials science, finance, and drug discovery.